In recent years, there has been a growing interest in location determination of emitters (e.g., transmitters) in urban canyons and in indoor venues where line of sight (LOS) conditions usually do not exist. In these cases, the propagation from the wireless emitter to the receiving antennas usually undergoes reflections from buildings and walls, referred to as multipath. Consequently, the multipath signals arriving at the receiving antennas may be very different from the LOS path. As a result, the classical position location techniques are not valid. Fingerprinting techniques have been developed to overcome this multipath problem.
Two types of fingerprinting techniques have been developed about the same time. The first is described by Wax et al. in U.S. Pat. Nos. 6,026,304, 6,064,339, 6,112,095, and 6,249,680, which are all incorporated herein by reference. This technique is based on using the multipath characteristics coherently received by a multiple-antenna base station (BS) as the location fingerprint. The other fingerprinting technique is described by Bahl and Padmanabhan in “RADAR: an in-building RF-based user location and tracking system”, INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE, 2000, vol. 2, pp. 775-784. This technique is based on using the received signal strength (RSS) obtained at several BSs as the location fingerprint.
The basic premise of multipath fingerprinting is that, in rich multipath environments, the multipath characteristics of the signals impinging on an antenna array—the directions-of-arrival and the differential-delays of the impinging multipath reflections—provide a unique “fingerprint” of the emitter location. In other words, there exists a “one-to-one” correspondence between the location of the emitter and the characteristics of the multipath signals emitting from this location and impinging on antenna array.
Fingerprinting algorithms are based on the premise that there is a one-to-one correspondence between the emitter location and the signal characteristics of the received multipath signals, i.e., that a fingerprint (or signature) can be extracted from the signal and serve as a unique identifier of the location. The localization problem is casted as a pattern recognition problem, namely, a database of fingerprints (or a fingerprints database”) is pre-collected in the desired area to be covered, and the location is determined by comparing the extracted fingerprint to the fingerprint database.
A key element in multipath fingerprinting is the fingerprint extraction method. Some extraction methods known in the art can be regarded as “descriptive methods”. One such descriptive method, referred to as Signal-Subspace Projection (SSP), is based on a projecting the received data on a low-dimensional subspace wherein the multipath signals reside, referred to as the signal-subspace. This projection matrix provides an effective description of the multipath characteristics of each location. Yet, the fact that it captures only the description of each location, without taking into consideration the description of the other locations in the database, is a deficiency.